Behavior Of Systems Research Articles

Decomposition solutions and Bäcklund transformations of the B-type and C-type Kadomtsev–Petviashvili equations

This paper introduces a modified formal variable separation approach, showcasing a systematic and notably straightforward methodology for analyzing the B-type Kadomtsev–Petviashvili (BKP) equation. Through the application of this approach, we successfully ascertain decomposition solutions, Bäcklund transformations, the Lax pair, and the linear superposition solution associated with the aforementioned equation. Furthermore, we expand the utilization of this technique to the C-type Kadomtsev–Petviashvili (CKP) equation, leading to the derivation of decomposition solutions, Bäcklund transformations, and the Lax pair specific to this equation. The results obtained not only underscore the efficacy of the proposed approach, but also highlight its potential in offering a profound comprehension of integrable behaviors in nonlinear systems. Moreover, this approach demonstrates an efficient framework for establishing interrelations between diverse systems.

Advancing interactive systems with liquid crystal network-based adaptive electronics.

Achieving adaptive behavior in artificial systems, analogous to living organisms, has been a long-standing goal in electronics and materials science. Efforts to integrate adaptive capabilities into synthetic electronics traditionally involved a typical architecture comprising of sensors, an external controller, and actuators constructed from multiple materials. However, challenges arise when attempting to unite these three components into a single entity capable of independently coping with dynamic environments. Here, we unveil an adaptive electronic unit based on a liquid crystal polymer that seamlessly incorporates sensing, signal processing, and actuating functionalities. The polymer forms a film that undergoes anisotropic deformations when exposed to a minor heat pulse generated by human touch. We integrate this property into an electric circuit to facilitate switching. We showcase the concept by creating an interactive system that features distributed information processing including feedback loops and enabling cascading signal transmission across multiple adaptive units. This system responds progressively, in a multi-layered cascade to a dynamic change in its environment. The incorporation of adaptive capabilities into a single piece of responsive material holds immense potential for expediting progress in next-generation flexible electronics, soft robotics, and swarm intelligence.

Tribocorrosion Evaluation of AISI 431 Coated With Tungsten Oxynitride

Abstract Tribocorrosion is a phenomenon present in a wide variety of processes; hence, understanding the tribocorrosion behavior of different systems is essential to being able to design robust and reliable systems. This has led us to investigate the tribocorrosion behavior of AISI 431 steel, a stainless steel commonly used for manufacturing mechanical pieces. The response to tribocorrosion was evaluated for the AISI 431 steel in contact with an aqueous solution of citric acid, a solution commonly used in the food industry. The tests were carried out using samples of steel uncoated and coated with tungsten oxynitride in a pin-on-disc configuration using a tailored tribocorrosion cell. The uncoated AISI 431 presented good wear and corrosion resistance but presented tribocorrosion degradation, where the growth of the passivation film and the mechanical removal of such film were the driving factors for the tribocorrosion process. Furthermore, when the steel was coated with the tungsten oxynitride film, we found that the surface presented a better resistance to wear, corrosion, and tribocorrosion. Such findings open a great opportunity for the use of these types of coatings to protect systems against tribocorrosion.

Self-Assembly of Lamellae-in-Lamellae by Double-Tail Cationic Surfactants.

The molecular structures of surfactants play a pivotal role in influencing their self-assembly behaviors. In this work, using simulations and experiments, an unconventional hierarchically layered structure in the didodecyldimethylammonium bromide (DDAB)/water binary system: lamellae-in-lamellae is revealed, a new self-assembly structure in surfactant system. This self-assembly structure refers to a lamellar structure with a shorter periodic length (inner lamellae) embedded in a lamellar phase with a longer periodic length (outer lamellae). The normal vectors of these two lamellar regions orient perpendicularly. In addition, it is observed that this lamellar-in-lamellar phase disappears when the two tails of the cationic surfactants become longer. The formation of the lamellar-in-lamellar architecture arises from multiple interacting factors. The key element is that the short tails of the DDAB surfactants enhance hydrophilicity and rigidity, which facilitates the formation of the inner lamellae. Moreover, the lateral monolayer of the inner lamellae provides shielding from the water and prompts the formation of the outer lamellae. These findings indicate that molecular structures and flexibility can profoundly redirect the hierarchical self-assembly behaviors in amphiphilic systems. More broadly, this work presents a new strategy to deliberately program hierarchical nanomaterials by designing specific surfactant molecules to act as tunable scaffolds, reactors, andcarriers.

Enhancing the performance of zero energy buildings with boosted coyote optimization and elman neural networks

This research paper aims to optimize electrical system modeling to minimize CO2 emissions, improve reliability, and reduce costs. It proposes integrating Elman Neural Network (ENN) and metaheuristic algorithm to evaluate environmental impact and optimize system performance. The goal is to create a mathematical model considering renewable energy sources, grid energy, CO2 emissions, and maintenance costs, and use metaheuristic algorithms to determine the optimal combination of wind turbines and photovoltaic panels. To train the ENN model and optimize the system, a three-stage approach is proposed. Quasi-random numbers are generated using Sobol techniques to create input data, which is then processed by TRNSYS for simulation. The proposed approach incorporates an ENN with Boosted version of the Coyote optimization algorithm to accurately model and predict the behavior of Hybrid Renewable Energy Systems for Zero Energy Buildings. The results demonstrate the effectiveness of the proposed approach. Our method significantly reduces energy consumption, costs, and system reliability, achieving a 25% reduction in energy consumption and 12% reduction in system cost, and is effective in optimizing hybrid solar/wind and hydrogen storage systems. The optimal system configuration significantly reduces CO2 emissions, achieves a high level of system reliability, and minimizes costs. Comparative analysis with previous studies showcases the superiority of the proposed method in achieving comprehensive optimization. In conclusion, this study combines AI techniques and metaheuristic algorithms to optimize electrical system design, considering environmental, technical, and economic factors. The proposed approach overcomes limitations in previous studies and offers an effective solution to address the optimization problem.

Data-Driven ICS Network Simulation for Synthetic Data Generation

Data-Driven ICS Network Simulation for Synthetic Data Generation

Data-Driven Initial Gap Identification of Piecewise-Linear Systems Using Sparse Regression and Universal Approximation Theorem

Abstract This paper proposes a method for identifying an initial gap in piecewise-linear (PWL) systems from data. Piecewise-linear systems appear in many engineered systems such as degraded mechanical systems and infrastructures and are known to show strong nonlinearities. To analyze the behavior of such piecewise-linear systems, it is necessary to identify the initial gap, at which the system behavior switches. The proposed method identifies the initial gap by discovering the governing equations using sparse regression and calculating the gap based on the universal approximation theorem. A key step to achieve this is to approximate a piecewise-linear function by a finite sum of piecewise-linear functions in sparse regression. The equivalent gap is then calculated from the coefficients of the multiple piecewise-linear functions and their respective switching points in the obtained equation. The proposed method is first applied to a numerical model to confirm its applicability to piecewise-linear systems. Experimental validation of the proposed method has then been conducted with a simple mass-spring-hopping system, where the method successfully identifies the initial gap in the system with high accuracy.

Chemical Potential Analysis as an Alternative to the van't Hoff Method: Hypothetical Limits of Solar Thermochemical Hydrogen.

The van't Hoff method is a standard approach for determining reaction enthalpies and entropies, e.g., in the thermochemical reduction of oxides, which is an important process for solar thermochemical fuels and numerous other applications. However, by analyzing the oxygen partial pressure pO2, e.g., as measured by thermogravimetric analysis (TGA), this method convolutes the properties of the probe gas with the solid-state properties of the examined oxides, which define their suitability for specific applications. The "chemical potential method" is here proposed as an alternative. Using the oxygen chemical potential ΔμO instead of pO2 for the analysis, this method does not only decouple gas-phase and solid-state contributions but also affords a simple and transparent approach to extracting the temperature dependence of the reduction enthalpy and entropy, which carries important information about the defect mechanism. For demonstration of the approach, this work considers three model systems; (1) a generic oxide with noninteracting, charge-neutral oxygen vacancy defects, (2) Sr0.86Ce0.14MnO3(1-δ) alloys with interacting vacancies, and (3) a model for charged vacancy formation in CeO2, which reproduces the extensive experimental TGA data available in the literature. The reduction behavior of these model systems obtained from the chemical potential method is correlated with simulated results for the thermochemical water splitting cycle, highlighting the exceptional behavior of CeO2, which originates from defect ionization. The theoretical performance limits for solar thermochemical hydrogen within the charged defect mechanism are assessed by considering hypothetical materials described by a variation of the CeO2 model parameters within a plausible range.

A New Concept for Interpretation of the Viscoelastic Behavior of Aqueous Sodium Carboxymethyl Cellulose Systems.

Viscoelastic behaviors of aqueous systems of commercially available sodium carboxymethyl cellulose (NaCMC) samples with the degrees of substitution (DS) of approximately 0.68 and 1.3, and the weight-average molar masses (Mw) higher than 200 kg mol-1 dissolved in pure water and aqueous sodium chloride solutions were investigated over a wide concentration (c) range of NaCMC samples. The dependencies of the specific viscosity (ηsp), the average relaxation time (τw), and the reciprocal of the steady-state compliance (Je-1) on c were discussed. The relationships ηsp ∝ c3, τw ∝ c2, and Je-1 ∝ c, characteristic of the rod particle suspensions, were clearly observed in a range lower than the c where the critical gel behavior was observed. Thus, a new concept based on the rheology of rod particle suspensions was employed to interpret the viscoelastic behaviors obtained in the c range. In this context, NaCMC polymer molecules are assumed to behave as extended rod particles with length (L) and diameter (d), including effective electrostatic repulsive distances, due to the dissociation of Na+ in aqueous systems. Thus, the number density of polymer molecules is given to be ν = c/Mw, and viscoelastic parameters such as ηsp, τw, and Je-1 are calculated using the theoretical model for rod particle suspensions proposed by Doi and Edwards. This concept reasonably described not only the viscoelastic data obtained in this study but also those from other groups using NaCMC samples with different DS and Mw values.

Beyond Dynamics: Learning to Discover Conservation Principles

Abstract The discovery of conservation principles is crucial for understanding the fundamental behavior of both classical and quantum physical systems across numerous domains. This paper introduces an innovative method that merges representation learning and topological analysis to explore the topology of conservation law spaces. Notably, the robustness of our approach to noise makes it suitable for complex experimental setups and its aptitude extends to the analysis of quantum systems, as successfully demonstrated in our paper. We exemplify our method’s potential to unearth previously unknown conservation principles and endorse interdisciplinary research through a variety of physical simulations. In conclusion, this work emphasizes the significance of data-driven techniques in deepening our comprehension of the principles governing classical and quantum physical systems.

Single file motion of robot swarms

We present experimental results on the single file motion of a group of robots interacting with each other through position sensors. We successfully replicate the fundamental diagram typical of these systems, with a transition from free flow to congested traffic as the density of the system increases. In the latter scenario we also observe the characteristic stop-and-go waves. The unique advantages of this novel system, such as experimental stability and repeatability, allow for extended experimental runs, facilitating a comprehensive statistical analysis of the global dynamics. Above a certain density, we observe a divergence of the average jam duration and the average number of robots involved in it. This discovery enables us to precisely identify another transition: from congested intermittent flow (for intermediate densities) to a totally congested scenario for high densities. Beyond this finding, the present work demonstrates the suitability of robot swarms to model complex behaviors in many particle systems. Published by the American Physical Society 2024

Magnesium isotope behavior in oceanic magmatic systems: Constraints from mid-ocean ridge lavas from the East Pacific Rise

The magnesium (Mg) isotope composition of oceanic basalts has provided useful constraints on the evolution of the upper mantle and crust-mantle interactions. However, the behavior of Mg isotopes during oceanic magma differentiation is still unclear because of the small range in Mg isotope values in typical normal mid-ocean ridge basalts (N-MORB). Here, we present high-precision Mg isotope data on a well-characterized suite of mid-ocean ridge (MOR) lavas from the 9–10°N segment of the East Pacific Rise. These samples range from relatively primitive basalt to evolved dacite with MgO contents decreasing from 8.62 to 0.80 wt.%, and display a resolvable variation in δ26Mg from -0.27 to -0.17‰. The less-evolved samples (MgO > 7.0 wt.%) that have experienced olivine and plagioclase fractional crystallization have δ26Mg values ranging from -0.23 to -0.17‰ that are negatively correlated with MgO content. Samples containing MgO of 3.5–7.0 wt.%, that have experienced significant crystallization of clinopyroxene, together with plagioclase, show a limited variation of δ26Mg (-0.20 to -0.18‰). For those highly evolved samples (MgO < 3.5 wt.%) saturated with Fe–Ti oxides, the δ26Mg vary from -0.27 to -0.20‰ and are positively correlated with MgO content. The variation of δ26Mg in the MOR lavas is consistent with three stages of magma differentiation, beginning with fractional crystallization of olivine and plagioclase followed by increasing amounts of clinopyroxene and finally joined by Fe-Ti oxides. Quantitative modeling of the Mg isotopic variation in EPR samples, shows that the variation of δ26Mg in MOR lavas is primarily a consequence of fractional crystallization of the Mg-bearing minerals when Δ26MgOl-melt ∼ -0.10‰, Δ26MgCpx-melt ∼ 0.00‰, and Δ26MgTi−Mgt-melt ∼ 0.20‰. This study provides evidence that shallow level crystal fractionation can produce significant and predicable variations in Mg isotopic compositions of MOR lavas and that this process should be carefully considered when using evolved lavas to trace mantle source compositions.

Simulation and experimental study of grid-connected photovoltaic power plants in a hot desert climate with fixed and dual-axis tracking

ABSTRACT This paper presents a comprehensive investigation into the performance of grid-connected photovoltaic (PV) power plants situated in a hot desert climate. The study employs a combination of simulation models and experimental data to assess the impact of two tracking systems – fixed and dual-axis – on the overall efficiency and energy yield of the PV installations. Through detailed simulations, we analyze the dynamic behavior of the PV systems under varying solar irradiance and the atmospheric conditions typical of hot desert environments. The dual-axis tracking system is compared against the conventional fixed-mount system to evaluate its effectiveness in maximizing energy production and improving the overall efficiency of the PV power plants. Experimental data collected from an actual grid-connected PV facility in a hot desert region is incorporated to validate the simulation results and enhance the accuracy of the study. The observed performance metrics include energy output, system reliability, and the impact of environmental factors on long-term sustainability. In general, in all weather conditions, solar tracking provides better yields than a fixed solar module, generating about 32% and 12% more energy in sunny and overcast weather conditions, respectively. Under sunny weather, the two-axis sun tracking system and a fixed tilt angle produce 333.228 kWh and 247.56 kWh of energy, respectively. The energy yield generated on a partly cloudy day by a two-axis sun tracking system and a fixed tilt angle PV system is 281.496 kWh and 257.856 kWh, respectively. In addition, the highest electricity gain for two-axis solar trackers versus fixed PV plants was found to be 34.6%, and the lowest value was found to be 9.16%. The experimental analysis shows that the efficiency of the polycrystalline PV module is 12% and 14% on sunny days and cloudy days, respectively. The comparison between fixed and dual-axis tracking systems contributes to the optimization of PV installations, enabling more informed decisions for sustainable energy production in regions characterized by high temperatures and intense solar radiation. To support the expanding applications of grid-tied PV systems with a sun tracker in the same or comparable location and climate conditions (Saharan environment), these studies have the practical utility of advising and offering helpful feedback to engineers, system designers, contractors, and investors.

Apathy and Depression Among People Aging With Traumatic Brain Injury: Relationships to Cognitive Performance and Psychosocial Functioning.

Apathy and depression are both common after moderate to severe traumatic brain injury (TBI) and may be especially important to distinguish in older adults with TBI. The authors examined apathy and depression in relation to cognitive performance domains and their potentially unique contribution to psychosocial functioning in this patient population. A total of 106 participants (mean±SD age=64±8 years) with chronic moderate to severe TBI (≥1 year) completed questionnaires assessing severity of apathy (Frontal Systems Behavior Scale-apathy subscale) and depression (Geriatric Depression Scale-15) symptoms, health-related quality of life (HRQoL), and societal participation. Participants also completed neuropsychological tests of episodic memory, processing speed, and executive functioning. Apathy symptom severity was significantly associated with all cognitive performances in correlations adjusted for the familywise error rate; a relationship with executive functioning remained after controlling for demographic and injury variables. Depression symptom severity was not significantly associated with cognition after statistical correction. Both symptomatologies uniquely contributed to HRQoL. Only depression symptoms contributed to societal participation. On the basis of clinical cutoffs, half the sample had neither depression nor apathy, approximately 25% met criteria for only apathy, and 25% had both apathy and depression. The combined presence of clinical depression and apathy was associated with worse HRQoL and societal participation. This is the first study to examine apathy and depression in relation to cognition and psychosocial functioning in an older sample with a history of TBI. Findings suggest that the two syndromes can be dissociated in clinically meaningful ways, which may help to refine psychiatric and behavioral interventions in this vulnerable population.

Non-Hermitian CHSH* game with a single trapped-ion qubit

Abstract The Clauser-Horne-Shimony-Holt (CHSH) game provides a captivating illustration of the advantages of quantum strategies over classical ones. In a recent study, a variant of the CHSH game leveraging a single qubit system, referred to as the CHSH* game, has been identified. We demonstrate that this mapping relationship between these two games remains effective even for a non-unitary gate. In this context, we delve into the breach of Tsirelson’s bound in a nonHermitian system, predicting changes in the upper and lower bounds of the player’s winning probability when employing quantum strategies in a single dissipative qubit system. We experimentally explore the impact of the CHSH* game on the player's winning probability in a single trapped-ion dissipative system, demonstrating a violation of Tsirelson's bound under the influence of parity-time (PT) symmetry. These results contribute to a deeper understanding of the influence of non-Hermitian systems on quantum games and the behavior of quantum systems under PT symmetry, which is crucial for designing more robust and efficient quantum protocols.

Analysis of Nonlinear Vibration Characteristics and Whirl Behavior of Dual-Rotor Systems with Inter-Shaft Rub Impact

Previous studies on rub-impact faults have mainly focused on the rub-impact between rotors and stators, with less research on inter-rotor rub impact. The impact of inter-rotor rub impact on rotor nonlinear vibration is particularly significant. This study investigates the effects of inter-shaft rub impact on the vibration characteristics and whirl behavior of dual-rotor systems. Initially, a dual-rotor model with inter-shaft bearings is established using the finite element method, and inter-shaft rub-impact forces are derived based on contact mechanics. Next, the system response is solved using the Newmark method. Vibration characteristics are analyzed through Campbell diagrams, 3D waterfall plots, time-frequency domain plots, and steady-state rub-impact force plots. Finally, the influence of inter-shaft rub impact on the whirl behavior of the dual-rotor system is studied based on the theory of full-spectrum analysis. The study concludes that inter-shaft rub-impact faults shift the system’s resonance points backward, increase harmonic and combination frequency components, and significantly affect the system response under dual-rotor co-rotation. Excessive friction can lead to self-excited vibrations and sudden amplitude increases, particularly in the LP rotor frequency. Additionally, inter-shaft rub impact primarily affects the whirl behavior of the LP-compressor disk1, showing multiple cycles of forward and backward whirl alternation during acceleration due to combined unbalanced and rub-impact excitations.

MICROPOLAR FLUID FLOWS RELATIVE TO A SWARM OF SPHERICAL POROUS SHELLS

This article investigates the creeping axisymmetric flow of an incompressible micropolar fluid past a swarm of porous shells. Employing the Darcy and a transition Brinkman porous layer, the study presents an analytical model that captures the flow behavior by integrating continuity conditions for velocity, normal and tangential stresses, and microrotations at fluid-porous interface regions.Distinct unit cell techniques, including those proposed by Happel, Kuwabara, Kvashnin, and Mehta and Morse, are analyzed to observe the effects of hydraulic resistivity, porous layer thickness, and porosity on the dimensionless drag for a bounded micropolar fluid system. The results, graphically represented in a series of plots, reveal a complex interplay between these parameters, significantly impacting drag forces and providing insight into the hydrodynamics of a swarm of porous particles, akin to that encountered in oral drug delivery systems.The study identifies a general inverse relationship between hydraulic resistivity and drag and highlights the nuanced effects of porous layer thickness and porosity on fluid resistance, with stark contrasts observed among different unit cell models. These findings underscore the importance of the chosen unit cell technique in predicting and optimizing the flow behavior in micropolar fluid systems.

Reentrant phase behavior in systems with density-induced tunneling

We show that correlations in strongly interacting many-particle systems can create quantum decoherence, leading to a mechanism of dissipation that does not rely on an external source. Using analytical methods, we study a bosonic many body system in two dimensions, with extended interactions between particles. We show that, as expected, the system can be driven out of a coherent state. Surprisingly, when the interaction strength is sufficiently large, the system reenters the superfluid phase even after coherence is lost. The breakdown of quantum coherence is a certainty, but interpreting the process correctly relies on understanding and preserving the nature of the coupling between the constituents of the many particle system. The methods used provide a natural cutoff point at the critical temperature, where superfluidity breaks down.

Experimental study on enhancing electrostatic charging of nonwoven filter media through novel electrode configurations

The COVID-19 pandemic has underscored the urgent need for efficient particle filtration to tackle public health challenges. This study compares the electrostatic charging capabilities of two types of electrodes: conventional Metal Lamellar Electrodes (MLE) and Modified Lamellar Plate Electrodes (MLPE) with PMMA insulation, in their role of charging nonwoven polypropylene filter media. Experimental analysis unequivocally demonstrates the superiority of MLPE in promoting effective electrostatic charge, as influenced by applied high voltage and inter-electrode distance, resulting in a significant enhancement in fine particle filtration. Numerical simulations of the electric field conducted using the COMSOL software and employing the Finite Element Method (FEM) validate these findings. FEM discretizes the domain into small finite elements and applies Laplace's equation in charge-free regions, providing a comprehensive understanding of the behavior of dual-electrode corona discharge systems. These simulations indicate higher field intensities for MLPE compared to MLE.By integrating experimental and numerical analyses, this study sheds light on the potential benefits of MLPE for air filtration systems, offering a noteworthy advancement in the control of airborne infections and reduction of environmental health risks. This research lays the groundwork for the development of more efficient and durable filtration systems, meeting the increasing demands for public health protection.The findings of this study suggest that the adoption of MLPE could significantly contribute to improving indoor air quality and mitigating the transmission of respiratory diseases. MLPE may also find utility in industrial filtration and air purification in sensitive work environments. Ultimately, this research sets the stage for the development of more efficient and sustainable filtration systems, addressing the growing needs for public health protection.

Direct and indirect switch from semiconductor to metallic behavior defined by the competition between Cation–Anion–Cation and Cation–Cation interactions leading to an important technological aspect of perovskite systems

We discuss in this work the key interactions that explain the possible electrical behaviors in different perovskite systems. Multi-behavior observation characterizes each frequency and temperature dependence of various perovskite systems. We classify such observations according to the temperature regimes. Indeed, a direct switch from semiconductor to metallic feature describes the conductivity evolution indicating the direct change from the localized (cation–anion–cation interactions) to delocalized (cation–cation interactions) state. The metallic character is reached due to the reinforcement of charge delocalization effect at high temperatures and frequencies. An indirect transformation separated by a frequency-independent regime is equally observed and discussed. Subsequently, a mixed regime is described by the conductivity temperature-independence which is explored at a specific frequency. Such investigations lead to demonstrate basic and common rules relevant for oxide-perovskites multi-behavior. Equally, important technological aspects are confirmed for systems that displays such multi-behavior character according to the temperature range.